Testing modern web and mobile applications often requires interacting with user interfaces that change dynamically. Elements may appear, disappear, or alter their properties based on user actions, asynchronous data loading, or other runtime conditions. This dynamic nature poses a significant challenge for automated testing, especially in model-driven testing frameworks where tests are generated or guided by abstract models representing the application’s behaviour.
This blog explores strategies, best practices, and considerations for effectively handling dynamic UI elements within model-driven tests (MDT). The goal is to help testers and developers design resilient, maintainable tests that can adapt to UI changes without frequent manual intervention.
Understanding Dynamic UI Elements
Dynamic UI elements are components that can change their presence, structure, or attributes at runtime. Examples include:
1. Menus or dialogs that appear only after a user click
2. Lists or tables that load asynchronously and change size or content
3. Elements that have IDs or classes generated dynamically
4. Components that change visibility or state based on user roles or settings
Because their properties are not fixed, traditional static locators (like fixed IDs or XPath expressions) may fail or become brittle when UI changes.
Challenges in Model-Driven Testing with Dynamic UI
Model-driven testing relies on abstract representations - state machines, flow models, or behaviour trees - that map out possible user interactions and system states. When the UI changes dynamically:
1. The model may not anticipate all possible states or transitions.
2. Locators encoded in the model may become invalid or ambiguous.
3. Timing issues arise when elements take time to load or appear.
4. Tests can become flaky, failing intermittently without code changes.
Addressing these challenges requires flexible strategies both at the model level and in the test execution layer.
Strategies for Handling Dynamic UI Elements
1. Use Robust Locators with Dynamic Attributes
Avoid relying solely on fixed IDs or absolute XPaths. Instead:
1. Leverage relative XPaths anchored to stable parent elements.
2. Use CSS classes combined with other attributes like text content or ARIA labels.
3. Identify elements uniquely by applying data-* attributes meant for testing.
4. Use regular expressions or partial matches when attributes contain dynamic parts.
2. Incorporate Waits and Synchronization
Dynamic elements may appear after variable delays. To handle this:
1. Implement explicit waits that wait for conditions like visibility, click ability, or presence of elements.
2. Fixed delays should be avoided, as they slow down tests and can cause inconsistent results.
3. Integrate wait logic into the model transitions that require element presence.
3. Model UI States and Transitions Explicitly
Update the model to capture the evolving states of the user interface:
1. Represent modal dialogs or dynamic panels as distinct states.
2. Model optional transitions for elements that may or may not appear.
3. Use UI element presence to annotate transitions with appropriate conditions or constraints.
This enables model-driven test generators to produce paths that reflect realistic UI flows.
4. Parameterize Locators in the Model
Where element attributes vary, parameterize locators:
1. Introduce variables or placeholders in the model to represent dynamic elements.
2. Resolve these parameters at runtime based on context or data inputs.
3. This reduces duplication and makes models adaptable to UI variations.
5. Use AI or Heuristic-Based Element Identification
In complex cases, AI-driven tools can help:
1. Identify elements through visual characteristics or by comparing similarities.
2. Apply heuristics that combine multiple attributes to locate targets.
3. Some model-driven frameworks support plugin extensions for this.
6. Maintain Test and Model Synchronization
When UI changes, update the model and test code in tandem:
1. Map model elements to UI components in a straightforward and traceable way.
2. Automate detection of locator breakages and surface them early.
3. Use version control and review processes to manage updates.
Best Practices Summary
1. Prioritize stable, maintainable locators over brittle absolute paths.
2. Model dynamic UI behaviour explicitly to reflect real application flows.
3. Integrate synchronization and waits into both the model and test execution.
4. Parameterize and abstract locator details within the model.
5. Regularly update models and test artifacts as the UI evolves.
6. Consider advanced techniques like AI-assisted element detection when needed.
Conclusion
Handling dynamic UI elements in model-driven tests demands a blend of thoughtful model design, flexible locator strategies, and solid synchronization practices. By explicitly modeling dynamic states, using parameterized and robust locators, and embedding waits smartly, testers can build automated tests that stay reliable amid UI changes. This approach reduces maintenance overhead and enhances confidence in test results, making model-driven testing a powerful method for complex, modern applications.